Machine Vision Algorithms and Applications

Передня обкладинка
John Wiley & Sons, 12 бер. 2018 р. - 516 стор.
Die zweite Auflage dieses erfolgreichen Lehrbuchs zum maschinellen Sehen ist vollständig aktualisiert, überarbeitet und erweitert, um die Entwicklungen der vergangenen Jahre auf den Gebieten der Bilderfassung, Algorithmen des maschinellen Sehens und dessen Anwendungen zu berücksichtigen. Hinzugekommen sind insbesondere neue Kameratechniken und Schnittstellen, 3D-Sensorik und -technologie, 3D-Objekterkennung und 3D-Bildrekonstruktion. Die Autoren folgen weiterhin dem Ansatz "soviel Theorie wie nötig, soviel Anwendungsbezug wie möglich". Alle Beispiele basieren auf der aktuellen Version der Software HALCON, von der nach Registrierung auf der Autorenwebseite eine Testversion erhältlich ist.
 

Зміст

PAL phase alternating line 56
1
FFT fast Fourier transform 124
2
Image Acquisition
5
BCS base coordinate system 324 325 336 337
9
compact disk 134 135 377 378 380 383
49
PLL phaselocked loop 58
58
CLProtocol Camera Link Protocol 62 73 77
62
GenApi Generic application programming interface for configuring cameras
63
SCARA Selective Compliant Arm for Robot Assembly 335 336
275
IO inputoutput 2 3 63 64 71 74
319
SSD sum of squared gray value differences 250254 263 264 267 271 275
333
SVM support vector machine 359 361364
359
Machine Vision Applications
371
References
461
extensible markup language 63 65 69 71 73 74 79
462
DHCP Dynamic Host Configuration Protocol 70
463

USB Universal Serial Bus 2 5 55 65 6770
67
GPU graphics processing unit 369
71
CMOS complementary metaloxide semiconductor 11 41 4652 54
91
Machine Vision Algorithms
97
DCS distributed control system 2
123
RANSAC random sample consensus 208 209
208
SAD sum of absolute gray value differences 250254 263267 271 275
250

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Про автора (2018)

Carsten Steger studied computer science at the Technical University of Munich (TUM) and received his PhD degree from TUM in 1998. In 1996, he co-founded the company MVTec, where he heads the Research department. He has authored and co-authored more than 80 scientific publications in the field of computer and machine vision. In 2011, he was appointed a TUM honorary professor for the field of computer vision.

Markus Ulrich studied Geodesy and Remote Sensing at the Technical University of Munich (TUM) and received his PhD degree from TUM in 2003. In 2003, he joined MVTec?s Research and Development department as a software engineer and became head of the research team in 2008. He has authored and co-authored scientific publications in the fields of photogrammetry and machine vision. Markus Ulrich is also a guest lecturer at TUM, where he teaches close-range photogrammetry. In 2017, he was appointed a Privatdozent (lecturer) at the Karlsruhe Institute of Technology (KIT) for the field of machine vision.

Christian Wiedemann studied Geodesy and Remote Sensing at the Technical University of Munich (TUM) and received his PhD degree from TUM in 2001. He has authored and co-authored more than 40 scientific publications in the fields of photogrammetry, remote sensing, and machine vision. In 2003, he joined MVTec's Research and Development department as a software engineer. Since 2008, he has held different leading positions at MVTec.

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